The exemplary embodiment relates to the field of image processing. It finds particular application in connection with the automated enhancement of digital images, and is described with particular reference thereto. However, it is to be appreciated that it may find more general application in image classification, image content analysis, and so forth.
Widespread availability of devices capable of acquiring digital images, such as digital cameras, cell phones, and other direct-digital imagers, and of optical scanners that convert film images, paper-printed images, and the like into digital format, has led to generation of large numbers of digital images. Regardless of the final medium in which the images will be managed, shared and visualized, the quality expectations of users are growing.
Digital images containing snow, however, often do not meet the user's expectations. This may be the result of the digital camera selecting incorrect settings which can result in underexposed or unnatural bluish pictures. The general assumption is that the average color of a photo should be gray. As a result, cameras compensate for what is assumed to be excess whiteness of the snow to the detriment of other darker colors. The resulting image appears flat and the snow dark. In other cases, the snow can look bluish when shooting under a blue sky, due to the scattering of light by the sky and the reflection from the snow of the bluish light.
To compensate for dark images, experienced photographers may manually overexpose when shooting in snow, e.g., by using a rule of thumb of +½ stops, or they may select a snow/winter shooting mode in the camera. In extreme cases, gray card targets may be employed to set the exposure/color balance meters. These operations are often time consuming and may require a level of expertise that is typically not met by the amateur photographer.
Amateur photographers often make use of online photofinishing or other automated or semi-automated image enhancement tools to compensate for degradations in image quality. These tools may include contrast and edge enhancement, noise filtering for a wide variety of noise sources, sharpening, exposure correction, color balance adjustment, automatic cropping, and correction of shaky images. Automated correction techniques, however, often fail to correct the problems associated with snow scenes or apply a correction which gives the image an unnatural appearance.
The exemplary embodiment overcomes these problems by providing automated techniques for improving the visual appearance of images containing snow.